AI Engineer in Bangalore driving innovation in Generative AI with expertise in RAG pipelines and Frontier Models.
About the role
- Principal Software & AI Architect at Blue Origin developing AI-driven solutions for rocket engines. Focused on product and SaaS solution architecture and enterprise guardrails.
Responsibilities
- Own end-to-end architecture for the AI application: domain model, APIs, UX/backend integration, data flows, and cloud/Kubernetes topology
- Define and implement multi-tenancy and isolation strategy (pooled vs. siloed vs. VPC), regionalization, and tenant-aware observability/support
- Establish SLAs/SLOs, rate limits/quotas, HA/DR, and resilience testing (chaos/failover); drive SLO/error-budget practices
- Build commercialization enablers: SSO (SAML/OIDC), SCIM provisioning, fine-grained RBAC/ABAC/DBAC, a zero-trust architected entitlement service
- Stand up ML Ops: data pipelines, feature store, model registry, CI/CD for ML, offline/online eval harness, model rollback/kill switches, human-in-the-loop workflows
- Security & privacy by design: threat modeling (including AI-specific risks), secrets/KMS, encryption at rest/in transit, audit logging, data retention/deletion, PII handling, secure SDLC controls (SAST/DAST/SBOM)
- Define BU architecture principles, capability map, and target state; publish reference architectures and an approved tech catalog
- Set identity and integration standards (API/eventing), data governance (lineage, quality, residency), and IaC patterns; create “paved roads” (golden templates for services, pipelines, observability, security checks, w/ auditability)
- Spin-out readiness: design boundary APIs with the parent company, plan data partitioning and key management
- Establish lightweight governance (Architecture Decision Records (ADRs), design reviews, fast exceptions) that enables speed while managing risk
- Mentor & support engineers on the team.
Requirements
- Minimum Bachelor's ideally Master's degree in Computer Science
- 10+ years in software architecture/engineering
- 5+ years leading architecture for customer-facing SaaS products
- Strong familiarity with AI and ML concepts
- Demonstrated experience shipping multi-tenant (or VPC-isolated) SaaS with defined SLAs and business customers
- Deep cloud/platform skills: containers/Kubernetes, IaC (e.g., Terraform), networking, CI/CD, observability, performance/cost optimization
- Security/compliance expertise: threat modeling, secure SDLC controls (SAST/DAST/SBOM), identity (OIDC/SAML) and provisioning (SCIM), audit logging; SOC 2 readiness or operation
- Data and AI/ML systems: data pipelines/governance, model lifecycle and MLOps, evaluation/guardrails, responsible AI practices
- Product mindset: understands packaging/entitlements, usage metering, versioning/compatibility, and impact on margins and customer experience
- Excellent communication and influence across executives, customers, and engineers; ability to create clarity and drive decisions in ambiguity.
Benefits
- Medical, dental, vision, basic and supplemental life insurance
- Paid parental leave
- Short and long-term disability
- 401(k) with a company match of up to 5%
- Education Support Program
- Paid Time Off: Up to four (4) weeks per year based on weekly scheduled hours, and up to 14 company-paid holidays.
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